Gartner Data & Analytics Summit 2026 Orlando: Day 1 Highlights

We are bringing you news and highlights from the Gartner Data & Analytics Summit, taking place this week in Orlando, Florida. Below is a collection of the key announcements and insights coming out of the conference. 

On Day 1 from the conference, we are highlighting the Gartner opening keynote presentation on navigating AI in the D&A journey to value, as well as sessions on designing the future-ready D&A organization, and practical ways to improve data governance. Be sure to check this page throughout the day for updates.

• Gartner Identifies Three Pillars for Deriving Value from AI

Presented by Adam Ronthal, VP Analyst, and Georgia O’Callaghan, Director Analyst, Gartner

AI is accelerating new possibilities for data and analytics everywhere. Success isn’t always about being the fastest, but about finding your own path to value, while managing risk and cost. Adam Ronthal, VP Analyst, and Georgia O’Callaghan, Director Analyst at Gartner, discussed how a thoughtful approach to speed and direction helps D&A leaders derive value from AI.

• “While more than half of IT leaders are concerned about cost overruns, fewer than one out of every five D&A or AI leaders are concerned that uncertain costs will limit AI value, and only 44% of organizations have adopted financial guardrails or AI FinOPs practices.”

• “D&A leaders must realize they are responsible for delivering real value in the midst of all this AI hype and fears of an AI bubble that might burst. Getting to value is often measured using ROI, which D&A leaders need to think of as more than just a financial measure.”

• “There are three ways to derive value from AI: 

  • Set AI ambition, providing a return on intelligence.

  • Strengthen AI foundations to achieve a return on integrity.

  • Empower people for AI transformation, contributing to a return on individuals.”

Journalists can read more in the press release “Gartner Identifies Three Pillars for Deriving Value from AI.”

Presented by Jorg Heizenberg, VP Analyst, Gartner

To position their teams as a must-have discipline that can fulfill cross-functional use cases, D&A leaders must optimize their organizational model. The optimal model balances enterprisewide capabilities focused on enablement with decentralized needs focused on outcomes. In this session, Jorg Heizenberg, VP Analyst at Gartner, discussed the design principles that underpin the ideal model and how D&A leaders can strike a balance between centralized consistency and decentralized agility.

• “D&A leaders should avoid choosing between centralization or decentralization; instead, they should adopt both, centralizing some aspects and decentralizing others to best suit their organization’s needs.”
• “Instead of a single version, D&A leaders should establish multiple interconnected versions of the D&A organization (global, regional, local, and the next version), clearly defining the dependencies and accountabilities of various functions and how they collaborate, including delivering D&A initiatives through cross-functional and multi-disciplinary teams to ensure agility and consistency.”
• “To fully realize the value of AI capabilities, organizations need to shift their focus from organizing in roles to identifying the specific skills their teams require to support high-priority initiatives. To lay a foundation for career and talent planning, in addition to team/organization planning, they should ensure that they check for all skills and proficiency levels across all versions.”

Journalists can receive additional information and/or request an interview with the Gartner expert by contacting Meghan Moran at meghan.moran@gartner.com.

Presented by Nate Novosel, VP Analyst, Gartner

There are seven key reasons organizations struggle with effective data governance. In this session, Nate Novosel, VP Analyst at Gartner, explained what consistently goes wrong and offered practical solutions to help make data governance work.

• “Organizations with low data governance maturity are significantly more likely to be among the organizations that will fail to realize AI value in the near future.”
• Practical ways to improve data governance:
  • Understand the purpose behind data governance in the organization. D&A leaders should start by identifying business outcomes first.
  • Deliver incremental value. Focus effort on prioritized business outcomes to accelerate ROI and minimize the required effort.
  • Rebrand governance as a team sport to help secure the necessary participants’ involvement in data governance activities.
  • Embed governance and culture activity into business workstreams as part of normal operations. Only 26% of organizations incorporate culture and communication into their D&A governance strategy.

Journalists can receive additional information and/or request an interview with the Gartner expert by contacting Meghan Moran at meghan.moran@gartner.com.